There are numerous examples in nature where individuals from various species obtain valuable information relating to other target individuals of their own or a different species, based on volatile substances released to the environment by the target. Such cues may originate from specialized organs, as those producing insect pheromones, or from more common sources such as breath, skin, urine, etc. Mosquitoes, for instance, use CO2 from breath as well as skin volatiles to identify their preys. Many mammals use also urine cues to mark and monitor their territory. Such olfactive information may be used not only to mark territory, find a mate, or locate a prey. Dogs are able to identify concrete individuals based on the sense of smell, and are used by their masters in a great diversity of functions, such as sensing cancers, explosives or drugs.
Key to the success of biological olfaction are the following characteristics:                1) Sensitivity (the ability to sense a particular vapor present at very small concentration);        2) Selectivity (the ability to distinguish the smell of one vapor from that of another, even when the interfering vapor may be far more abundant);        3) Speed (the ability to sense, recognize, and react rapidly to particular vapors and vapor patterns, ideally in real time);        4) Effective pattern recognition strategies.        
Humans have attempted to compensate for their relatively poor sense of smell with a range of olfaction devices. Some have been relatively fast, including desorption electrospray ionization DESI (Takáts et al. 2004), its variant extractive electrospray ionization EESI (aimed at ionizing aerosolized samples; Chen et al. 2006) and so called DART (Cody et al. 2005). These approaches have been applied to the study of skin (or membrane in the case of cells or bacteria) substances. For instance Chen et al. (2007) have used a variant of DESI (EESI) to monitor continuously the release of caffeine from the skin of a person before and after drinking three cups of coffee. Song et al. (2007) have monitored DESI ions from intact bacteria. Their observation of acilium ions (acid minus OH) from hexadecanoic and octadecanoic acids is particularly interesting, given the known possibility to distinguish between various species of bacteria based on lipid analysis. Their direct approach is in interesting contrast with conventional bacterial analysis, involving a complex and destructive process of isolation and methylation of membrane fatty acids (Heller et al. 1987; Cole et al. 1991; Marr et al. 1962; Harrington et al. 1989). But these interesting studies have been used primarily to ionize condensed (rather than vapor) samples, and have neither shown high sensitivity to vapor species, nor revealed a particularly rich olfactive pattern from vapors naturally released into the ambient by either persons or other organisms. Relatively rich odor patterns have been observed in volatiles from breath or skin via gas chromatography-mass spectrometry (GC-MS). But GC-MS is not fast, and its most impressive use in skin or breath analysis has required even slower sample collection and preconcentration (Bernier et al. 2000; Gallagher et al. 2008). Another much faster but less sensitive method (in the range of parts-per-billion (ppb); Smith et al. 2005) is so-called selected ion flow tube-mass spectrometry (SIFT-MS). SIFT-MS has provided real-time information on skin emanations on relatively simple molecules of high vapor pressure, such as acetone (Turner et al. 2008). Also, some other relatively light skin species have been detected in vivo with a more sensitive technique (parts-per-trillion, ppt; Lindinger et al. 1998), so-called proton transfer reaction/mass spectrometry (PTR-MS; Steeghsa et al. 2006).
Earlier fast techniques specifically designed to ionize volatiles at atmospheric pressure have been used following pioneering studies based on corona discharges (Lane et al. 1981). An alternative atmospheric charging approach has been based on mixing the vapors of interest with a cloud of small highly charged drops produced by electrospray ionization (ESI). The method, pioneered by Fenn (Whitehouse et al. 1986; Fuerstenau et al. 1999) and Hill (Wu et al. 2000; Tam et al. 2004), and used by Lee and Shiea (1998), has been referred to as secondary ESI (SESI). The inventors herein have used a slight variant of this approach in U.S. patent application Ser. No. 11/732,770, in a charger embodiment where gas is sampled from the ambient, and mixed with the charged cloud of an electrospray of a solvent/buffer relatively free from involatile solutes. U.S. patent application Ser. No. 11/732,770 is incorporated by reference herein in its entirety. Polar volatile species contained in this sampled gas are then ionized, either directly by the charged electrosprayed drops, or by the ions released by evaporation of these drops. The ionized vapors are then analyzed in an atmospheric pressure ionization mass spectrometer (API-MS) or another analytical instrument having an atmospheric pressure source. This approach has been used to analyze human breath in positive ionization (Martínez-Lozano el al. 2007). The method was clearly shown to be fast and sensitive, and revealed relatively complex mass spectra. However, several difficulties arose precluding the observation of sufficiently rich and clearly interpretable olfactive patterns enabling a sophisticated recognition processes (as those occurring in the biological world). One serious difficulty in investigations of dilute vapors in ambient gas is the great number of volatile species present in the atmosphere, even at large distances from any concrete organism. Distinguishing this rich background from the signal vapors originating from the organism is therefore a large part of the problem. Martínez-Lozano et al. (2007) separated the signal and the background by subtracting the mass spectrum obtained from ambient air from that obtained from exhaled air. However, this subtraction method may lead to false results (Martínez-Lozano and Fernández de la Mora. 2008, 2009). Breath has generally a much higher humidity than ambient air, yet, humidity has a large effect on the probability of ionization of many vapors (particularly many of those released by the skin). In order for the mass-spectrum correction to be effective, the background sample needs to be brought to a humidity level similar to that of the real sample. As a result, no prior work has been able to analyze vapors released into the ambient by any organism under the desired conditions matching the sensitivity, selectivity, and speed of sensing and recognizing typical, for instance, of dogs. Either the pattern obtained was rich but the measurement was slow (as in Bernier et al., or Gallhager et al.), or the measurement was fast but the pattern found was either insufficiently rich, or not rapidly interpretable. Accordingly, the purpose of this invention is to provide a means to sense and classify organisms with characteristics comparable to that of the dog, or even better.